BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

233 related articles for article (PubMed ID: 30854457)

  • 1. Explaining Deep Features Using Radiologist-Defined Semantic Features and Traditional Quantitative Features.
    Paul R; Schabath M; Balagurunathan Y; Liu Y; Li Q; Gillies R; Hall LO; Goldgof DB
    Tomography; 2019 Mar; 5(1):192-200. PubMed ID: 30854457
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semantic characteristic grading of pulmonary nodules based on deep neural networks.
    Liu C; Zhao R; Pang M
    BMC Med Imaging; 2023 Oct; 23(1):156. PubMed ID: 37833636
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.
    Sihong Chen ; Jing Qin ; Xing Ji ; Baiying Lei ; Tianfu Wang ; Dong Ni ; Jie-Zhi Cheng
    IEEE Trans Med Imaging; 2017 Mar; 36(3):802-814. PubMed ID: 28113928
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
    Huang W; Xue Y; Wu Y
    PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Expert knowledge-infused deep learning for automatic lung nodule detection.
    Tan J; Huo Y; Liang Z; Li L
    J Xray Sci Technol; 2019; 27(1):17-35. PubMed ID: 30452432
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Representation of Deep Features using Radiologist defined Semantic Features.
    Paul R; Liu Y; Li Q; Hall L; Goldgof D; Balagurunathan Y; Schabath M; Gillies R
    Proc Int Jt Conf Neural Netw; 2018 Jul; 2018():. PubMed ID: 30443437
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.
    Tran GS; Nghiem TP; Nguyen VT; Luong CM; Burie JC
    J Healthc Eng; 2019; 2019():5156416. PubMed ID: 30863524
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Unboxing AI - Radiological Insights Into a Deep Neural Network for Lung Nodule Characterization.
    Venugopal VK; Vaidhya K; Murugavel M; Chunduru A; Mahajan V; Vaidya S; Mahra D; Rangasai A; Mahajan H
    Acad Radiol; 2020 Jan; 27(1):88-95. PubMed ID: 31623996
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Incorporating automatically learned pulmonary nodule attributes into a convolutional neural network to improve accuracy of benign-malignant nodule classification.
    Dai Y; Yan S; Zheng B; Song C
    Phys Med Biol; 2018 Dec; 63(24):245004. PubMed ID: 30524071
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.
    Zhang C; Sun X; Dang K; Li K; Guo XW; Chang J; Yu ZQ; Huang FY; Wu YS; Liang Z; Liu ZY; Zhang XG; Gao XL; Huang SH; Qin J; Feng WN; Zhou T; Zhang YB; Fang WJ; Zhao MF; Yang XN; Zhou Q; Wu YL; Zhong WZ
    Oncologist; 2019 Sep; 24(9):1159-1165. PubMed ID: 30996009
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pulmonary nodule detection in CT scans with equivariant CNNs.
    Winkels M; Cohen TS
    Med Image Anal; 2019 Jul; 55():15-26. PubMed ID: 31003034
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.
    Choe J; Lee SM; Do KH; Lee G; Lee JG; Lee SM; Seo JB
    Radiology; 2019 Aug; 292(2):365-373. PubMed ID: 31210613
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.
    Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J
    J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Hyperparameter optimization and development of an advanced CNN-based technique for lung nodule assessment.
    Shivwanshi RR; Nirala N
    Phys Med Biol; 2023 Aug; 68(17):. PubMed ID: 37567211
    [No Abstract]   [Full Text] [Related]  

  • 15. A Novel Hybrid Feature Extraction Model for Classification on Pulmonary Nodules.
    Kailasam SP; Sathik MM
    Asian Pac J Cancer Prev; 2019 Feb; 20(2):457-468. PubMed ID: 30803208
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.
    Ren Y; Tsai MY; Chen L; Wang J; Li S; Liu Y; Jia X; Shen C
    Int J Comput Assist Radiol Surg; 2020 Feb; 15(2):287-295. PubMed ID: 31768885
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multi-scale Convolutional Neural Networks for Lung Nodule Classification.
    Shen W; Zhou M; Yang F; Yang C; Tian J
    Inf Process Med Imaging; 2015; 24():588-99. PubMed ID: 26221705
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping.
    Lei Y; Tian Y; Shan H; Zhang J; Wang G; Kalra MK
    Med Image Anal; 2020 Feb; 60():101628. PubMed ID: 31865281
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT.
    Xie Y; Zhang J; Xia Y
    Med Image Anal; 2019 Oct; 57():237-248. PubMed ID: 31352126
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A semantic fidelity interpretable-assisted decision model for lung nodule classification.
    Zhan X; Long H; Gou F; Wu J
    Int J Comput Assist Radiol Surg; 2024 Apr; 19(4):625-633. PubMed ID: 38141069
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.